| dc.contributor.advisor | Sierra Araujo, Basilio  | |
| dc.contributor.advisor | Arganda Carreras, Ignacio | |
| dc.contributor.author | Salinas Colina, Josu | |
| dc.contributor.other | F. INFORMATICA | |
| dc.contributor.other | INFORMATIKA F. | |
| dc.date.accessioned | 2018-10-15T17:58:16Z | |
| dc.date.available | 2018-10-15T17:58:16Z | |
| dc.date.issued | 2018-10-15 | |
| dc.identifier.uri | http://hdl.handle.net/10810/29096 | |
| dc.description.abstract | Trainable Superpixel Segmentation is a plug-in developed for the ImageJ platform that aims at providing its users with the ability to train models to segment images by classifying superpixels using region-based image features. This project provides an underlying library that can be used independently, a graphic interface for ease of use and an evaluation protocol of the efficacy of the library. The evaluation of the developed library was conducted through a ten-fold cross-validation and the results were compared with those of the Trainable Weka Segmentation library. | es_ES |
| dc.language.iso | eng | es_ES |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | machine learning | es_ES |
| dc.subject | computer vision | es_ES |
| dc.subject | pixel classification | es_ES |
| dc.subject | image segmentation | es_ES |
| dc.subject | superpixel classification | es_ES |
| dc.title | Trainable superpixel segmentation | es_ES |
| dc.type | info:eu-repo/semantics/bachelorThesis | |
| dc.date.updated | 2018-06-18T08:01:42Z | |
| dc.language.rfc3066 | es | |
| dc.rights.holder | © 2018, el autor | |
| dc.contributor.degree | Grado en Ingeniería Informática | es_ES |
| dc.contributor.degree | Informatikaren Ingeniaritzako Gradua | |
| dc.identifier.gaurregister | 87888-776118-10 | |
| dc.identifier.gaurassign | 77061-776118 | |
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